The increase of the world's population located near areas prone to natural disasters has given rise to new ‘mega risks’; the rebuild after disasters will test the governments’ capabilities to provide appropriate responses to protect the people and businesses. During the aftermath of the Christchurch earthquakes (2010-2012) that destroyed much of the inner city, the government of New Zealand set up a new partnership between the public and private sector to rebuild the city’s infrastructure. The new alliance, called SCIRT, used traditional risk management methods in the many construction projects. And, in hindsight, this was seen as one of the causes for some of the unanticipated problems. This study investigated the risk management practices in the post-disaster recovery to produce a specific risk management model that can be used effectively during future post-disaster situations. The aim was to develop a risk management guideline for more integrated risk management and fill the gap that arises when the traditional risk management framework is used in post-disaster situations. The study used the SCIRT alliance as a case study. The findings of the study are based on time and financial data from 100 rebuild projects, and from surveying and interviewing risk management professionals connected to the infrastructure recovery programme. The study focussed on post-disaster risk management in construction as a whole. It took into consideration the changes that happened to the people, the work and the environment due to the disaster. System thinking, and system dynamics techniques have been used due to the complexity of the recovery and to minimise the effect of unforeseen consequences. Based on an extensive literature review, the following methods were used to produce the model. The analytical hierarchical process and the relative importance index have been used to identify the critical risks inside the recovery project. System theory methods and quantitative graph theory have been used to investigate the dynamics of risks between the different management levels. Qualitative comparative analysis has been used to explore the critical success factors. And finally, causal loop diagrams combined with the grounded theory approach has been used to develop the model itself. The study identified that inexperienced staff, low management competency, poor communication, scope uncertainty, and non-alignment of the timing of strategic decisions with schedule demands, were the key risk factors in recovery projects. Among the critical risk groups, it was found that at a strategic management level, financial risks attracted the highest level of interest, as the client needs to secure funding. At both alliance-management and alliance-execution levels, the safety and environmental risks were given top priority due to a combination of high levels of emotional, reputational and media stresses. Risks arising from a lack of resources combined with the high volume of work and the concern that the cost could go out of control, alongside the aforementioned funding issues encouraged the client to create the recovery alliance model with large reputable construction organisations to lock in the recovery cost, at a time when the scope was still uncertain. This study found that building trust between all parties, clearer communication and a constant interactive flow of information, established a more working environment. Competent and clear allocation of risk management responsibilities, cultural shift, risk prioritisation, and staff training were crucial factors. Finally, the post-disaster risk management (PDRM) model can be described as an integrated risk management model that considers how the changes which happened to the environment, the people and their work, caused them to think differently to ease the complexity of the recovery projects. The model should be used as a guideline for recovery systems, especially after an earthquake, looking in detail at all the attributes and the concepts, which influence the risk management for more effective PDRM. The PDRM model is represented in Causal Loops Diagrams (CLD) in Figure 8.31 and based on 10 principles (Figure 8.32) and 26 concepts (Table 8.1) with its attributes.
Coastal and river environments are exposed to a number of natural hazards that have the potential to negatively affect both human and natural environments. The purpose of this research is to explain that significant vulnerabilities to seismic hazards exist within coastal and river environments and that coasts and rivers, past and present, have played as significant a role as seismic, engineering or socio-economic factors in determining the impacts and recovery patterns of a city following a seismic hazard event. An interdisciplinary approach was used to investigate the vulnerability of coastal and river areas in the city of Christchurch, New Zealand, following the Canterbury Earthquake Sequence, which began on the 4th of September 2010. This information was used to identify the characteristics of coasts and rivers that make them more susceptible to earthquake induced hazards including liquefaction, lateral spreading, flooding, landslides and rock falls. The findings of this research are applicable to similar coastal and river environments elsewhere in the world where seismic hazards are also of significant concern. An interdisciplinary approach was used to document and analyse the coastal and river related effects of the Canterbury earthquake sequence on Christchurch city in order to derive transferable lessons that can be used to design less vulnerable urban communities and help to predict seismic vulnerabilities in other New Zealand and international urban coastal and river environments for the future. Methods used to document past and present features and earthquake impacts on coasts and rivers in Christchurch included using maps derived from Geographical Information Systems (GIS), photographs, analysis of interviews from coastal, river and engineering experts, and analysis of secondary data on seismicity, liquefaction potential, geology, and planning statutes. The Canterbury earthquake sequence had a significant effect on Christchurch, particularly around rivers and the coast. This was due to the susceptibility of rivers to lateral spreading and the susceptibility of the eastern Christchurch and estuarine environments to liquefaction. The collapse of river banks and the extensive cracking, tilting and subsidence that accompanied liquefaction, lateral spreading and rock falls caused damage to homes, roads, bridges and lifelines. This consequently blocked transportation routes, interrupted electricity and water lines, and damaged structures built in their path. This study found that there are a number of physical features of coastal and river environments from the past and the present that have induced vulnerabilities to earthquake hazards. The types of sediments found beneath eastern Christchurch are unconsolidated fine sands, silts, peats and gravels. Together with the high water tables located beneath the city, these deposits made the area particularly susceptible to liquefaction and liquefaction-induced lateral spreading, when an earthquake of sufficient size shook the ground. It was both past and present coastal and river processes that deposited the types of sediments that are easily liquefied during an earthquake. Eastern Christchurch was once a coastal and marine environment 6000 years ago when the shoreline reached about 6 km inland of its present day location, which deposited fine sand and silts over this area. The region was also exposed to large braided rivers and smaller spring fed rivers, both of which have laid down further fine sediments over the following thousands of years. A significant finding of this study is the recognition that the Canterbury earthquake sequence has exacerbated existing coastal and river hazards and that assessments and monitoring of these changes will be an important component of Christchurch’s future resilience to natural hazards. In addition, patterns of recovery following the Canterbury earthquakes are highlighted to show that coasts and rivers are again vulnerable to earthquakes through their ability to recovery. This city’s capacity to incorporate resilience into the recovery efforts is also highlighted in this study. Coastal and river areas have underlying physical characteristics that make them increasingly vulnerable to the effects of earthquake hazards, which have not typically been perceived as a ‘coastal’ or ‘river’ hazard. These findings enhance scientific and management understanding of the effects that earthquakes can have on coastal and river environments, an area of research that has had modest consideration to date. This understanding is important from a coastal and river hazard management perspective as concerns for increased human development around coastlines and river margins, with a high seismic risk, continue to grow.
When disasters and crises, both man-made and natural, occur, resilient higher education institutions adapt in order to continue teaching and research. This may necessitate the closure of the whole institution, a building and/or other essential infrastructure. In disasters of large scale the impact can be felt for many years. There is an increasing recognition of the need for disaster planning to restructure educational institutions so that they become more resilient to challenges including natural disasters (Seville, Hawker, & Lyttle, 2012).The University of Canterbury (UC) was affected by seismic events that resulted in the closure of the University in September 2010 for 10 days and two weeks at the start of the 2011 academic year This case study research describes ways in which e-learning was deployed and developed by the University to continue and even to improve learning and teaching in the aftermath of a series of earthquakes in 2010 and 2011. A qualitative intrinsic embedded/nested single case study design was chosen for the study. The population was the management, support staff and educators at the University of Canterbury. Participants were recruited with purposive sampling using a snowball strategy where the early key participants were encouraged to recommend further participants. Four sources of data were identified: (1) documents such as policy, reports and guidelines; (2) emails from leaders of the colleges and academics; (3) communications from senior management team posted on the university website during and after the seismic activity of 2010 and 2011; and (4) semi-structured interviews of academics, support staff and members of senior management team. A series of inductive descriptive content analyses identified a number of themes in the data. The Technology Acceptance Model 2 (Venkatesh & Davis, 2000) and the Indicator of Resilience Model (Resilient Organisations, 2012) were used for additional analyses of each of the three cases. Within the University case, the cases of two contrasting Colleges were embedded to produce a total of three case studies describing e-learning from 2000 - 2014. One contrast was the extent of e-learning deployment at the colleges: The College of Education was a leader in the field, while the College of Business and Law had relatively little e-learning at the time of the first earthquake in September 2010. The following six themes emerged from the analyses: Communication about crises, IT infrastructure, Availability of e-learning technologies, Support in the use of e-learning technologies, Timing of crises in academic year and Strategic planning for e-learning. One of the findings confirmed earlier research that communication to members of an organisation and the general public about crises and the recovery from crises is important. The use of communication channels, which students were familiar with and already using, aided the dissemination of the information that UC would be using e-learning as one of the options to complete the academic year. It was also found that e-learning tools were invaluable during the crises and facilitated teaching and learning whilst freeing limited campus space for essential activities and that IT infrastructure was essential to e-learning. The range of e-learning tools and their deployment evolved over the years influenced by repeated crises and facilitated by the availability of centrally located support from the e-Learning support team for a limited set of tools, as well as more localised support and collaboration with colleagues. Furthermore, the reasons and/or rate of e-learning adoption in an educational institution during crises varied with the time of the academic year and the needs of the institution at the time. The duration of the crises also affected the adoption of e-learning. Finally, UC’s lack of an explicit e-learning strategy influenced the two colleges to develop college-specific e-learning plans and those College plans complemented the incorporation of e-learning for the first time in the University’s teaching and learning strategy in 2013. Twelve out of the 13 indicators of the Indicators of Resilience Model were found in the data collected for the study and could be explained using the model; it revealed that UC has become more resilient with e-learning in the aftermath of the seismic activities in 2010 and 2011. The interpretation of the results using TAM2 demonstrated that the adoption of technologies during crises aided in overcoming barriers to learning at the time of the crisis. The recommendations from this study are that in times of crises, educational institutions take advantage of Cloud computing to communicate with members of the institution and stakeholders. Also, that the architecture of a university’s IT infrastructure be made more resilient by increasing redundancy, backup and security, centralisation and Cloud computing. In addition, when under stress it is recommended that new tools are only introduced when they are essential.